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8th IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES)

作者： Biswal, Saubhagya Ranjan Shankar, Gauri Indian Sch Mines Indian Inst Technol Elect Engn Dept Dhanbad Bihar India

ISBN: (纸本)9781538693155

The present work implements sine cosine algorithm (SCA) for obtaining optimal location and size of capacitor banks for addressing problems like voltage instability and line losses in radial distribution systems. By using power loss index (PLI) method, the buses that are more sensitive to the capacitor placement are identified and, thereafter, the location and size are optimized by using proposed SCA. The main objective of the system is considered as the minimization of the total cost. The algorithm is implemented on 33 bus and 69 bus test systems and the results obtained are compared with those yielded using other algorithms.

关键词： capacitor placement power loss index radial distribution system sine cosine algorithm

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PID Controller Design Based on sine cosine algorithm for Magnetic Ball Suspension System

PID Controller Design Based on Sine Cosine Algorithm for Mag...

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International Conference on Artificial Intelligence and Data Processing (IDAP)

作者： Ozaydin, Cihat Zeynelgil, Hatice Late Ekinci, Serdar Hekimoglu, Baran Batman Univ Dept Comp Engn Batman Turkey Istanbul Tech Univ Dept Elect Engn Istanbul Turkey Batman Univ Dept Elect & Elect Engn Batman Turkey

ISBN: (纸本)9781728129334;9781728129327

In this study, a new approach to control the position of the ball in the magnetic suspension system is proposed and a proportional + integral + derivative (PID) controller is designed. By using the sine cosine algorithm (SCA), the optimal PID controller parameters were obtained by minimizing a new objective function, which consists of the integral of the time-weighted squared error (ITSE) performance index and the overshoot. With this proposed approach, the performance of the system is improved optimally specifically in terms of settling time and overshoot. The effectiveness of the proposed SCA-based controller was verified by comparisons made with the artificial bee colony (ABC) algorithm-based and wind driven optimization (WDO) algorithm-based controllers (in terms of convergence curves, pole/zero map, transient response and performance index).

关键词： sine cosine algorithm magnetic suspension system PID controller optimization

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Bearing Fault Diagnosis Using Support Vector Classifier Based on sine cosine algorithm 33

Bearing Fault Diagnosis Using Support Vector Classifier Base...

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33rd Chinese Control and Decision Conference (CCDC)

作者： Li, Sai Jiao, Rui Ding, Zhixia Wang, Liheng Ye, Xuan Wuhan Inst Technol Sch Elect & Informat Engn Wuhan 430205 Peoples R China CSSC Res Inst 722 Wuhan 430205 Peoples R China

ISBN: (纸本)9781665440899

In order to ensure the normal operation of rotating machinery, it is necessary and important to carry out fault diagnosis of rolling bearings. This paper proposes a fault diagnosis algorithm for rolling bearings, which is based on singular value decomposition with traditional empirical mode decomposition, and support vector classifier with sine cosine algorithm. First, empirical mode decomposition is utilized to characterize the complexity of vibration signals. Furthermore, singular value decomposition is applied to extract the fault feature. Subsequently, support vector classifier with sine cosine algorithm is proposed for fault recognition under various conditions. The performance of the proposed method has been verified by its successful application in rolling bearings experiments. Compared with the existing methods, this approach can detect bearings faults effectively, and improve the classification efficiency.

关键词： Fault diagnosis Rolling bearing Support vector classifier sine cosine algorithm

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A New Learnheuristic: Binary SARSA - sine cosine algorithm (BS-SCA) 8th

A New Learnheuristic: Binary SARSA - Sine Cosine Algorithm (...

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8th International Conference on Metaheuristics and Nature Inspired Computing (META)

作者： Becerra-Rozas, Marcelo Lemus-Romani, Jose Crawford, Broderick Soto, Ricardo Cisternas-Caneo, Felipe Trujillo Embry, Andres Arnao Molina, Maximo Tapia, Diego Castillo, Mauricio Rubio, Jose-Miguel Pontificia Univ Catolica Valparaiso Valparaiso Chile Pontificia Univ Catolica Chile Santiago Chile Univ Bernardo OHiggins Santiago Chile

ISBN: (纸本)9783030942168;9783030942151

This paper proposes a novel learnheuristic called Binary SARSA - sine cosine algorithm (BS-SCA) for solving combinatorial problems. The BS-SCA is a binary version of sine cosine algorithm (SCA) using SARSA to select a binarization operator. This operator is required due SCA was created to work in continuous domains. The performance of BS-SCA is benchmarked with a Q-learning version of the learnheuristic. The problem tested was the Set Covering Problem and the results show the superiority of our proposal.

关键词： Learnheuristic SARSA sine cosine algorithm Combinatorial problem

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Opposition-Based sine cosine algorithm (OSCA) for Training Feed-Forward Neural Networks 13

Opposition-Based Sine Cosine Algorithm (OSCA) for Training F...

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13th International Conference on Signal-Image Technology and Internet-Based Systems (SITIS)

作者： Bairathi, Divya Gopalani, Dinesh Malaviya Natl Inst Technol Jaipur Jaipur Rajasthan India

ISBN: (纸本)9781538642832

Neural network is an effective machine learning technique for classification and regression. In recent studies many stochastic population based techniques are applied to train neural networks. In this paper, Opposition-Based sine cosine algorithm (OSCA) is applied for feed-forward neural network (FNN) training. OSCA is a new population based metaheuristic, which is improved version of sine cosine algorithm (SCA) and uses the opposition based learning (OBL) for better exploration. Performance is analysed and compared with Particle Swarm Optimization (PSO), Differential Evolution (DE), Genetic algorithm (GA), Ant Colony Optimization (ACO) and Evolution Strategy (ES) for eight different datasets.

关键词： Optimization Metaheuristics stochastic optimization Opposition-Based sine cosine algorithm sine cosine algorithm Feed-forward neural networks - training Classification Regression

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Image Classification Based on BP Neural Network and sine cosine algorithm 10

Image Classification Based on BP Neural Network and Sine Cos...

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10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems - Technology and Applications (IDAACS)

作者： Song, Haoqiu Ye, Zhiwei Wang, Chunzhi Yan, Lingyu Hubei Univ Technol Sch Comp Sci Wuhan Hubei Peoples R China Fujian Prov Key Lab Data Intens Comp Fuzhou Peoples R China Fujian Prov Univ Key Lab Intelligent Comp & Informat Proc Fuzhou Peoples R China

ISBN: (纸本)9781728140698

Image classification is one of the most important tasks in image analysis and computer vision. BP neural network is a successful classifier for the task. However, with regard to the low study efficiency and the slow convergence speed in BP algorithm, some optimization algorithms have been proposed for achieving better results. Among all these methods, BP neural network improved by particle swarm optimization (PSO) and genetic algorithm (GA) may be the most successful and classical ones. Nevertheless, both GA and PSO are easy to fall into the local optimal solution, which has a great impact on the precision of classification. As a result, a novel optimization algorithm called sine cosine algorithm (SCA) is presented to improve the classification performance. The experimental results manifest that the proposed method has good performances, and the classification accuracy is better than BP neural network optimized by GA, PSO or other algorithms.

关键词： Image Classification BP Neural Network Evolutionary Computation sine cosine algorithm

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Optimal Reactive Power Dispatch Using Modified sine cosine algorithm

Optimal Reactive Power Dispatch Using Modified Sine Cosine A...

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International Conference on Innovative Trends in Computer Engineering (ITCE)

作者： Abdel-Fatah, Said Ebeed, Mohamed Kamel, Salah Egyptian Ferro Silicon Alloys Co Aswan Egypt Sohag Univ Fac Engn Dept Elect Engn Sohag Egypt

ISBN: (纸本)9781538652619

Solving the Optimal Reactive Power Dispatch (ORPD) problem in power system is a vital task to capture the most secure and stable operation of reactive power resources. In this paper, the ORPD problem is solved using a new modified sine cosine algorithm (MSCA). sine cosine algorithm (SCA) is a well-known population-based optimization technique. Despite the SCA is an effective algorithm, it may prone to stagnation and stuck in local minima for some cases. The modified sine cosine algorithm (MSCA) is based on Levy flight distribution with adaptive operators. This algorithm is developed to avoid the shortage of the conventional SCA and enhance its searching abilities. The considered objective functions are minimizing the power losses, improving the voltage profile and enhancing the stability of system. The proposed algorithm is applied to IEEE 30-bus system and the yielded results are compared with other well-known optimization algorithms. The simulation results demonstrate the superiority and efficiency of the MSCA for solving the ORPD compared to the other listed techniques in literature.

关键词： Optimal reactive power optimization ORPD sine cosine algorithm

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Improved Chaotic sine cosine algorithm (ICSCA) for global optima

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International Journal of Information Technology (Singapore) 2024年第1期16卷 245-260页

作者： Shinde, Vikas Jha, Rahul Mishra, Dilip Kumar Department of Mathematics and Computing Madhav Institute of Technology and Science Gwalior India

This paper deals with sine cosine algorithm to make a balance between exploration and exploitation of the search space and find best convergence rate for global optima, that are used the two trigonometric function sine and cosine for modification of solution. We present the improved version of sine cosine algorithm which provide the better exploration mechanism for search space and ten chaotic maps have merged with improved sine cosine algorithm to determine the better outcomes with efficacies as well as proposed work as compared to others algorithms and incorporate four engineering problems. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Chaotic maps Constrained benchmark optimization Engineering design optimization sine cosine algorithm

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Adaptive sine cosine algorithm Integrated with Differential Evolution for Structural Damage Detection 17th

Adaptive Sine Cosine Algorithm Integrated with Differential ...

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17th International Conference on Computational Science and its Applications (ICCSA)

作者： Bureerat, Sujin Pholdee, Nantiwat Khon Kaen Univ Sustainable & Infrastruct Res & Dev Ctr Dept Mech Engn Fac Engn Khon Kaen 40002 Thailand

ISBN: (纸本)9783319623924;9783319623917

A sine cosine algorithm is one promising meta-heuristic recently proposed. In this work, the algorithm is extended to be self-adaptive and its main reproduction operators are integrated with the mutation operator of differential evolution. The new algorithm is called adaptive sine cosine algorithm integrated with differential evolution (ASCA-DE) and used to tackle the test problems for structural damage detection. The results reveal that the new algorithm outperforms a number of established meta-heuristics.

关键词： sine cosine algorithm Differential evolution Structural damage detection Optimization Meta-heuristics

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Solving Multi-Task Optimization Problems using the sine cosine algorithm 2022

Solving Multi-Task Optimization Problems using the Sine Cosi...

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11th International Conference on Software and Computer Applications, ICSCA 2022

作者： Zamli, Kamal Z. Abdul Kader, Md. Faculty of Computing College of Computing and Applied Sciences Universiti Malaysia Pahang Pahang Pekan26600 Malaysia

ISBN: (纸本)9781450385770

Optimization problems relate to the problem of finding minimum or maximum values from a large pools of solutions whereby exhaustive search is practically impossible. Often, optimization problems are solved using metaheuristic algorithms which provide good enough solution within reasonable execution time and limited resources. Recently, much research focus in the literature is devoted on a new kind of optimization problem, called multi-task optimization (MTO). This paper highlights our on-going work dealing with MTO problem. More precisely, our work investigates the adoption of partitioned population based on sine cosine algorithm for dealing with MTO problem. We took the team formation problem from IMDB dataset as our case study based on two objectives, minimizing team costs and team load distribution. © 2022 ACM.

关键词： Multi-task Optimization sine cosine algorithm

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